Methods and organisms for growth-coupled production of 3-hydroxypropionic acid

ABSTRACT

The invention provides a non-naturally occurring microorganism having one or more gene disruptions, the one or more gene disruptions occurring in genes encoding an enzyme obligatory coupling 3-hydroxypropionic acid production to growth of the microorganism when the gene disruption reduces an activity of the enzyme, whereby the one or more gene disruptions confers stable growth-coupled production of 3-hydroxypropionic acid onto the non naturally occurring microorganism. The disruptions can be complete gene disruptions and the non-naturally occurring organisms can include a variety of prokaryotic or eukaryotic microorganisms. A method of producing a non-naturally occurring microorganism having stable growth-coupled production of 3-hydroxypropionic acid is further provided. The method includes: (a) identifying in silico a set of metabolic modifications requiring 3-hydroxypropionic acid production during exponential growth, and (b) genetically modifying a microorganism to contain the set of metabolic modifications requiring 3-hydroxypropionic acid production.

This application claims the benefit of priority of U.S. Provisionalapplication Ser. No. 60/897,004, filed Jan. 22, 2007, the entirecontents of which are incorporated herein by reference.

BACKGROUND OF THE INVENTION

This invention relates generally to in silico design of organisms and,more specifically to organisms having selected genotypes for thegrowth-coupled production of 3-hydroxypropionic acid (3-HP).

The compound 3-hydroxypropionic acid (3-hydroxypropionate or 3-HP) is athree-carbon carboxylic acid that has industrial potential as a buildingblock for a number of commodity and specialty chemicals. Compounds thatcan be produced from 3-HP by chemical synthesis include polymerprecursors such as acrylic acid, acrylamide, methyl acrylate, and1,3-propanediol; chemical intermediates such as malonic acid, and anumber alcohol esters of 3-HP. 3-HP itself also is used in thenutritional industry as a food preservative. Although the abovecompounds can be produced from petroleum feedstocks, the ability toproduce the entire family of 3-HP derived products from a platformchemical, preferably made from renewable resources, would be useful. Forthese reasons, it is among the set of twelve compounds identified by theDepartment of Energy as highest priority for the development ofbioprocesses out of over 300 evaluated candidates (DOE Report, “TopValue-Added Chemicals from Biomass”, 2004).

Several chemical synthesis routes have been described to produce 3-HP,and biocatalytic routes have also been disclosed (WO 01/16346 to Sutherset al). However, chemical synthesis of 3-HP is costly and inefficient.

Despite the efforts and reports purporting the development ofbiocatalytic routes for the production of 3-HP, the approaches employedhave several drawbacks which hinder applicability in commercialsettings. As described further below, the stains produced by the abovemethods can be unstable in commercial fermentation processes due toselective pressures favoring the unaltered or wild-type parentalcounterparts.

Thus, there exists a need for microorganisms having commerciallybeneficial characteristics that can efficiently produce commercialquantities of 3-HP. Obligatory linking biosynthesis of a desired productto optimal growth conditions is a further need that would becommercially beneficial. The present invention satisfies these needs andprovides related advantages as well.

SUMMARY OF THE INVENTION

The invention provides a non-naturally occurring microorganism havingone or more gene disruptions, the one or more gene disruptions occurringin genes encoding an enzyme obligatory coupling 3-hydroxypropionic acidproduction to growth of the microorganism when the gene disruptionreduces an activity of the enzyme, whereby the one or more genedisruptions confers stable growth-coupled production of3-hydroxypropionic acid onto the non-naturally occurring microorganism.Also provided is a non-naturally occurring microorganism comprising aset of metabolic modifications obligatory coupling 3-hydroxypropionicacid production to growth of the microorganism, the set of metabolicmodifications having disruption of one or more genes including: (a) theset of genes selected from: (1) adhE, ldhA, pta-ackA; (2) adhE, ldhA,frdABCD; (3) adhE, ldhA, frdABCD, ptsG; (4) adhE, ldhA, frdABCD, pntAB;(5) adhE, ldhA, fumA, fumB, fumC; (6) adhE, ldhA, fumA, fumB, fumC,pntAB; (7) pflAB, ldhA, or (8) adhE, ldhA, pgi in a microorganismutilizing an anaerobic β-alanine 3-HP precursor pathway; (b) the set ofgenes selected from: (1) tpi, zwf; (2) tpi, ybhE; (3) tpi, gnd; (4) fpb,gapA; (5) pgi, edd, or (6) pgi, eda in a microorganism utilizing anaerobic glycerol 3-HP precursor pathway; (c) the set of genes selectedfrom: (1) eno; (2) yibO; (3) eno, atpH, or other atp subunit, or (4)yibO, atpH, or other atp subunit, in a microorganism utilizing aglycerate 3-HP precursor pathway, or an ortholog thereof, wherein themicroorganism exhibits stable growth-coupled production of3-hydroxypropionic acid. The disruptions can be complete genedisruptions and the non-naturally occurring organisms can include avariety of prokaryotic or eukaryotic microorganisms. A method ofproducing a non-naturally occurring microorganism having stablegrowth-coupled production of 3-hydroxypropionic acid is furtherprovided. The method includes: (a) identifying in silico a set ofmetabolic modifications requiring 3-hydroxypropionic acid productionduring exponential growth, and (b) genetically modifying a microorganismto contain the set of metabolic modifications requiring3-hydroxypropionic acid production.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an estimated depiction of the tradeoff between biochemicalproduction and cell growth. Points A and B represent the maximum biomasssolution of the wild-type and mutant strains, respectively. Note thatthe mutant strain exhibits growth-coupled production.

FIG. 2 shows a bilevel optimization structure of OptKnock. The innerproblem performs the flux allocation based on the optimization of aparticular cellular objective. The outer problem then maximizes thebioengineering objective (e.g., compound overproduction) by restrictingaccess to key reactions available to the optimization of the innerproblem.

FIG. 3 shows a schematic diagram of 3-hydroxypropionic acid metabolismand routes for its biochemical synthesis.

FIG. 4 shows metabolic pathways leading from glycolytic intermediates to3-hydroxypropionic acid. The production routes through β-alanine,glycerol and glycerate are differentiated by thicker lines.

FIG. 5 shows the 3-HP versus growth rate boundaries for variousOptKnock-derived mutant strains (A: designs #1-4, B: designs #5-6)compared to the wild-type under anaerobic conditions. A basis glucoseuptake rate of 10 mmol/gDW/hr and a non-growth associated ATPrequirement of 7.6 mmol/gDW/hr were used for these simulations.

FIG. 6 shows the 3-HP versus growth rate boundaries for variousOptKnock-derived mutant strains (designs #7-10) compared to thewild-type under anaerobic conditions. A basis glucose uptake rate of 10mmol/gDW/hr and a non-growth associated ATP requirement of 7.6mmol/gDW/hr were used for these simulations.

FIG. 7 shows the 3-HP versus growth rate boundaries for variousOptKnock-derived mutant strains (designs #11-13) compared to thewild-type under anaerobic conditions. A basis glucose uptake rate of 10mmol/gDW/hr and a non-growth associated ATP requirement of 7.6mmol/gDW/hr were used for these simulations.

FIG. 8 shows the 3-HP versus growth rate boundaries for variousOptKnock-derived mutant strains (designs #14-16) compared to thewild-type under anaerobic conditions. A basis glucose uptake rate of 10mmol/gDW/hr and a non-growth associated ATP requirement of 7.6mmol/gDW/hr were used for these simulations. The abbreviation GLYCtsignifies that this solution boundary was calculated after constrainingglycerol production to be zero.

FIG. 9 shows the 3-HP versus growth rate boundaries for design #17 underconditions where the flux through glyceraldehyde-3-phosphatedehydrogenase (GAPD) can be limited. A basis glucose uptake rate of 10mmol/gDW/hr and a non-growth associated ATP requirement of 7.6mmol/gDW/hr were used for these simulations.

FIG. 10 shows the 3-HP versus growth rate boundaries for designs #2 and#18-20 under either (A) anaerobic or (B) aerobic conditions where theglycerate pathway to 3-HP is allowed to be active in E. coli. A basisglucose uptake rate of 10 mmol/gDW/hr and a non-growth associated ATPrequirement of 7.6 mmol/gDW/hr were used for these simulations.

DETAILED DESCRIPTION OF THE INVENTION

This invention is directed to the design and production of cells andorganisms having growth-coupled production of 3-hydroxypropionic acid(3-HP). In one embodiment, the invention utilizes optimization-basedapproaches based on in silico stoichiometric models of Escherichia colimetabolism that identify metabolic designs for optimal production of3-hydroxypropionic acid. A bilevel programming framework, OptKnock, isapplied within an iterative algorithm to predict multiple sets of genedisruptions, that collectively result in the growth-coupled productionof 3-hydroxypropionic acid. The results described herein indicate thatcombinations of strategically placed gene deletions or functionaldisruptions of genes significantly improves the 3-hydroxypropionic acidproduction capabilities of Escherichia coli and other cells ororganisms. Growth-coupled production of 3-hydroxypropionic acid for thein silico designs are confirmed by construction of strains having thedesigned metabolic genotype. These metabolically engineered cells ororganisms also can be subjected to adaptive evolution to further augmentgrowth-coupled 3-hydroxypropionic acid production, including underconditions approaching theoretical maximum growth.

In certain embodiments, deletions were placed such that the redundancyin the network was reduced with the ultimate effect of coupling growthto the production of 3-hydroxypropionic acid in the network. Further,the growth-coupled 3-hydroxypropionic acid production characteristics ofthe designed strains make them genetically stable and particularlyuseful in continuous bioprocesses. Separate strain design strategieswere identified with incorporation of different non-native reactioncapabilities into E. coli leading to 3-hydroxypropionic acid producingmetabolic pathways from either β-alanine, glycerol or glycerate.Hundreds of in silico metabolic designs were identified that increasedthe production of 3-hydroxypropionic acid. The top 20 designs wereselected for further characterization. One observed characteristic inmany of the 3-hydroxypropionic acid producing strain designs resultedfrom manipulation the cofactor availability in the network.

In a further embodiment, the invention is directed to an integratedcomputational and engineering platform for developing metabolicallyaltered microorganism strains having enhanced 3-hydroxypropionic acidproducing characteristics. Strains identified via the computationalcomponent of the platform are put into actual production by geneticallyengineering the predicted metabolic alterations which lead to theenhanced production of 3-hydroxypropionic acid. Production of3-hydroxypropionic acid is coupled to optimal growth of themicroorganism to optimize yields of this product during fermentation. Inyet a further embodiment, strains exhibiting growth-coupled productionof 3-hydroxypropionic acid are further subjected to adaptive evolutionto further augment product biosynthesis. The levels of growth-coupled3-hydroxypropionic acid production following adaptive evolution also canbe predicted by the computational component of the system where, in thisspecific embodiment, the elevated 3-hydroxypropionic acid levels arerealized only following evolution.

As used herein, the term “non-naturally occurring” when used inreference to a microorganism of the invention is intended to mean thatthe microorganism has at least one genetic alteration not normally foundin a wild-type strain of the referenced species. The genetic alterationcan be a gene deletion or some other functional disruption of thegenetic material.

As used herein, the term “microorganism” is intended to mean aprokaryotic or eukaryotic cell or organism having a microscopic size.The term is intended to include bacteria of all species and eukaryoticorganisms such as yeast and fungi. The term also includes cell culturesof any species that can be cultured for the production of a biochemical.

As used herein, the term “growth-coupled” when used in reference to theproduction of a biochemical is intended to mean that the biosynthesis ofthe referenced biochemical is an obligatory product produced during thegrowth phase of a microorganism.

As used herein, the term “metabolic modification” is intended to referto a biochemical reaction that is altered from its naturally occurringstate. Metabolic modifications can include, for example, elimination ofa biochemical reaction activity by functional disruptions of one or moregenes encoding an enzyme participating in the reaction. Sets ofexemplary metabolic modification are illustrated in Table 2. Reactantsand products utilized in these reactions are exemplified in Table 3.

As used herein, the term “3-hydroxypropionic acid” or “3-HP” is intendedto mean the carboxylic acid C₃H₆O₃ having a molecular mass of 90.08g/mol and a pKa of 4.5. It also is known in the art as hydracrylic acidand ethylene lactic acid. The term “3-hydroxypropionic acid” as it isused herein is intended to include any of its various3-hydroxypropionate salt forms. Chemically, 3-hydroxyproprionatecorresponds to a salt or ester of 3-hydroxypropionic acid. Therefore,3-hydroxypropionic acid and 3-hydroxypropionate refer to the samecompound, which can be present in either of the two forms depending onthe pH of the solution. Therefore, the terms 3-hydroxypropionic acid,3-hydroxypropionate and 3-HP as well as its other art recognized nameshydracrylic acid and ethylene lactic acid are used synonymously herein.

As used herein, the term “gene disruption,” or grammatical equivalentsthereof, is intended to mean a genetic alteration that renders theencoded gene product inactive. The genetic alteration can be, forexample, deletion of the entire gene, deletion of a regulatory sequencerequired for transcription or translation, deletion of a portion of thegene with results in a truncated gene product or by any of variousmutation strategies that inactivate the encoded gene product. Oneparticularly useful method of gene disruption is complete gene deletionbecause it reduces or eliminates the occurrence of genetic reversions inthe non-naturally occurring microorganisms of the invention.

As used herein, the term “stable” when used in reference togrowth-coupled production of a biochemical product is intended to referto microorganism that can be cultured for greater than five generationswithout loss of the coupling between growth and biochemical synthesis.Generally, stable growth-coupled biochemical production will be greaterthan 10 generations, particularly stable growth-coupled biochemicalproduction will be greater than about 25 generations, and moreparticularly, stable growth-coupled biochemical production will begreater than 50 generations, including indefinitely. Stablegrowth-coupled production of a biochemical can be achieved, for example,by deletion of a gene encoding an enzyme catalyzing each reaction withina set of metabolic modifications. The stability of growth-coupledproduction of a biochemical can be enhanced through multiple deletions,significantly reducing the likelihood of multiple compensatoryreversions occurring for each disrupted activity.

Those skilled in the art will understand that the metabolicmodifications exemplified herein are described with reference to E. coligenes and their corresponding metabolic reactions. However, given thecomplete genome sequencing of a wide variety of organisms and the highlevel of skill in the area of genomics, those skilled in the art willreadily be able to apply the teachings and guidance provided herein toessentially all other organisms. For example, the E. coli metabolicalterations exemplified herein can readily be applied to other speciesby incorporating the same or analogous gene disruptions in the otherspecies. Such disruptions can include, for example, genetic alterationsof species homologs, in general, and in particular, orthologs, paralogsor nonorthologous gene displacements.

An ortholog is a gene or genes that are related by vertical descent andare responsible for substantially the same or identical functions indifferent organisms. For example, mouse epoxide hydrolase and humanepoxide hydrolase can be considered orthologs for the biologicalfunction of hydrolysis of epoxides. Genes are related by verticaldescent when, for example, they share sequence similarity of sufficientamount to indicate they are homologous, or related by evolution from acommon ancestor. Genes can also be considered orthologs if they sharethree-dimensional structure but not necessarily sequence similarity, ofa sufficient amount to indicate that they have evolved from a commonancestor to the extent that the primary sequence similarity is notidentifiable. Genes that are orthologous can encode proteins withsequence similarity of about 25% to 100% amino acid sequence identity.Genes encoding proteins sharing an amino acid similarity less that 25%can also be considered to have arisen by vertical descent if theirthree-dimensional structure also shows similarities. Members of theserine protease family of enzymes, including tissue plasminogenactivator and elastase, are considered to have arisen by verticaldescent from a common ancestor.

Orthologs include genes or their encoded gene products that through, forexample, evolution, have diverged in structure or overall activity. Forexample, where one species encodes a gene product exhibiting twofunctions and where such functions have been separated into distinctgenes in a second species, the three genes and their correspondingproducts are considered to be orthologs. For the growth-coupledproduction of a biochemical product, those skilled in the art willunderstand that the orthologous gene harboring the metabolic activity tobe disrupted is to be chosen for construction of the non-naturallyoccurring microorganism. An example of orthologs exhibiting separableactivities is where distinct activities have been separated intodistinct gene products between two or more species or within a singlespecies. A specific example is the separation of elastase proteolysisand plasminogen proteolysis, two types of serine protease activity, intodistinct molecules as plasminogen activator and elastase. A secondexample is the separation of mycoplasma 5′-3′ exonuclease and DrosophilaDNA polymerase III activity. The DNA polymerase from the first speciescan be considered an ortholog to either or both of the exonuclease orthe polymerase from the second species and vice versa.

In contrast, paralogs are homologs related by, for example, duplicationfollowed by evolutionary divergence and have similar or common, but notidentical functions. Paralogs can originate or derive from, for example,the same species or from a different species. For example, microsomalepoxide hydrolase (epoxide hydrolase I) and soluble epoxide hydrolase(epoxide hydrolase II) can be considered paralogs because they representtwo distinct enzymes, co-evolved from a common ancestor, that catalyzedistinct reactions and have distinct functions in the same species.Paralogs are proteins from the same species with significant sequencesimilarity to each other suggesting that they are homologous, or relatedthrough co-evolution from a common ancestor. Groups of paralogousprotein families include HipA homologs, luciferase genes, peptidases,and others.

A nonorthologous gene displacement is a nonorthologous gene from onespecies that can substitute for a referenced gene function in adifferent species. Substitution includes, for example, being able toperform substantially the same or a similar function in the species oforigin compared to the referenced function in the different species.Although generally, a nonorthologous gene displacement will beidentifiable as structurally related to a known gene encoding thereferenced function, less structurally related but functionally similargenes and their corresponding gene products nevertheless will still fallwithin the meaning of the term as it is used herein. Functionalsimilarity requires, for example, at least some structural similarity inthe active site or binding region of a nonorthologous gene compared to agene encoding the function sought to be substituted. Therefore, anonorthologous gene includes, for example, a paralog or an unrelatedgene.

Therefore, in identifying and constructing the non-naturally occurringmicroorganisms of the invention having growth-coupled production of abiochemical, those skilled in the art will understand with applying theteaching and guidance provided herein to a particular species that theidentification of metabolic modifications should include identificationand disruption of orthologs. To the extent that paralogs and/ornonorthologous gene displacements are present in the referencedmicroorganism that encode an enzyme catalyzing a similar orsubstantially similar metabolic reaction, those skilled in the art alsocan eliminate these evolutionally related genes to ensure that anyfunctional redundancy in enzymatic activities do not short circuit thedesigned metabolic modifications.

Orthologs, paralogs and nonorthologous gene displacements can bedetermined by methods well known to those skilled in the art. Forexample, inspection of nucleic acid or amino acid sequences for twopolypeptides will reveal sequence identity and similarities between thecompared sequences. Based on such similarities, one skilled in the artcan determine if the similarity is sufficiently high to indicate theproteins are related through evolution from a common ancestor.Algorithms well known to those skilled in the art, such as Align, BLAST,Clustal W and others compared and determine a raw sequence similarity oridentity, and also determine the presence or significance of gaps in thesequence which can be assigned a weight or score. Such algorithms alsoare known in the art and are similarly applicable for determiningnucleotide sequence similarity or identity. Parameters for sufficientsimilarly to determine relatedness are computed based on well knownmethods for calculating statistical similarity, or the chance of findinga similar match in a random polypeptide, and the significance of thematch determined. A computer comparison of two or more sequences can, ifdesired, also be optimized visually by those skilled in the art. Relatedgene products or proteins can be expected to have a high similarity, forexample, 25% to 100% sequence identity. Proteins that are unrelated canhave an identity which is essentially the same as would be expected tooccur by chance, if a database of sufficient size is scanned (about 5%).Sequences between 5% and 24% may or may not represent sufficienthomology to conclude that the compared sequences are related. Additionalstatistical analysis to determine the significance of such matches giventhe size of the data set can be carried out to determine the relevanceof these sequences.

Exemplary parameters for determining relatedness of two or moresequences using the BLAST algorithm, for example, can be as set forthbelow. Briefly, amino acid sequence alignments can be performed usingBLASTP version 2.0.8 (Jan. 5, 1999) and the following parameters:Matrix: 0 BLOSUM62; gap open: 11; gap extension: 1; x_dropoff: 50;expect: 10.0; wordsize: 3; filter: on. Nucleic acid sequence alignmentscan be performed using BLASTN version 2.0.6 (Sep. 16, 1998) and thefollowing parameters: Match: 1; mismatch: −2; gap open: 5; gapextension: 2; x_dropoff: 50; expect: 10.0; wordsize: 11; filter: off.Those skilled in the art will know what modifications can be made to theabove parameters to either increase or decrease the stringency of thecomparison, for example, and determine the relatedness of two or moresequences.

The invention provides a method of producing a non-naturally occurringmicroorganism having stable growth-coupled production of3-hydroxypropionic acid. The method includes: (a) identifying in silicoa set of metabolic modifications requiring 3-hydroxypropionic acidproduction during exponential growth, and (b) genetically modifying amicroorganism to contain said set of metabolic modifications requiring3-hydroxypropionic acid production.

An important consideration for bioprocessing is whether to use a batchor continuous fermentation scheme. One difference between the twoschemes that will influence the amount of product produced is thepresence of a preparation, lag, and stationary phase for the batchscheme in addition to the exponential growth phase. In contrast,continuous processes are kept in a state of constant exponential growthand, if properly operated, can run for many months at a time. Forgrowth-associated and mixed-growth-associated product formation,continuous processes provide much higher productivities (i.e., dilutionrate times cell mass) due to the elimination of the preparation, lag,and stationary phases. For example, given the following reasonableassumptions:

Monod kinetics (i.e., μ=μ_(m)·S/(K_(s)+S))

μ_(m)=1.0 hr⁻¹

final cell concentration/initial cell concentration=20

t_(prep)+t_(lag)+t_(stat)=5 hr

feed concentration of limiting nutrient >> Ks

increased productivity from a continuous process has been estimated at8-fold, Shuler et al, Prentice Hall, Inc.: Upper Saddle River, N.J.,245-247.

Despite the overwhelming advantage in productivity, many more batchprocesses are in operation than continuous processes for a number ofreasons. First, for non-growth associated product formation (e.g.,penicillin), the productivity of a batch system may significantly exceedthat of a continuous process because the latter would have to operate atvery low dilution rates. Next, production strains generally haveundergone modifications to their genetic material to improve theirbiochemical or protein production capabilities. These specializedstrains are likely to grow less rapidly than their parental complementswhereas continuous processes such those employing chemostats (fermentersoperated in continuous mode) impose large selection pressures for thefastest growing cells. Cells containing recombinant DNA or carryingpoint mutations leading to the desired overproduction phenotype aresusceptible to back-mutation into the original less productive parentalstrain. It also is possible for strains having single gene deletions todevelop compensatory mutations that will tend to restore the wild-typegrowth phenotype. The faster growing cells usually out-compete theirmore productive counterparts for limiting nutrients, drasticallyreducing productivity. Batch processes, on the other hand, limit thenumber of generations available by not reusing cells at the end of eachcycle, thus decreasing the probability of the production strainreverting back to its wild-type phenotype. Finally, continuous processesare more difficult to operate long-term due to potential engineeringobstacles such as equipment failure and foreign organism contamination.The consequences of such failures also are much more considerable for acontinuous process than with a batch culture.

For small-volume production of specialty chemicals and/or proteins, theproductivity increases of continuous processes rarely outweigh the risksassociated with strain stability and reliability. However, for theproduction of large-volume, growth-associated products such as3-hydroxypropionic acid, the increases in productivity for a continuousprocess can result in significant economic gains when compared to abatch process. Although the engineering obstacles associated withcontinuous bioprocess operation would always be present, the strainstability concerns can be overcome through metabolic engineeringstrategies that reroute metabolic pathways to reduce or avoid negativeselective pressures and favor production of the target product duringthe exponential growth phase.

One computational method for identifying and designing metabolicalterations favoring growth-coupled production of a product is theOptKnock computational framework, Burgard et al., Biotechnol Bioeng, 84:647-57 (2003). OptKnock is a metabolic modeling and simulation programthat suggests gene deletion strategies that result in genetically stablemicroorganisms which overproduce the target product. Specifically, theframework examines the complete metabolic and/or biochemical network ofa microorganism in order to suggest genetic manipulations that force thedesired biochemical to become an obligatory byproduct of cell growth. Bycoupling biochemical production with cell growth through strategicallyplaced gene deletions or other functional gene disruption, the growthselection pressures imposed on the engineered strains after long periodsof time in a bioreactor lead to improvements in performance as a resultof the compulsory growth-coupled biochemical production. Lastly, whengene deletions are constructed there is a negligible possibility of thedesigned strains reverting to their wild-type states because the genesselected by OptKnock are to be completely removed from the genome.

Briefly, OptKnock is a term used herein to refer to a computationalmethod and system for modeling cellular metabolism. The OptKnock programrelates to a framework of models and methods that incorporate particularconstraints into flux balance analysis (FBA) models. These constraintsinclude, for example, qualitative kinetic information, qualitativeregulatory information, and/or DNA microarray experimental data.OptKnock also computes solutions to various metabolic problems by, forexample, tightening the flux boundaries derived through flux balancemodels and subsequently probing the performance limits of metabolicnetworks in the presence of gene additions or deletions. OptKnockcomputational framework allows the construction of model formulationsthat enable an effective query of the performance limits of metabolicnetworks and provides methods for solving the resulting mixed-integerlinear programming problems. The metabolic modeling and simulationmethods referred to herein as OptKnock are described in, for example,U.S. patent application Ser. No. 10/043,440, filed Jan. 10, 2002, and inInternational Patent No. PCT/US02/00660, filed Jan. 10, 2002.

Another computational method for identifying and designing metabolicalterations favoring growth-coupled production of a product is metabolicmodeling and simulation system termed SimPheny®. This computationalmethod and system is described in, for example, U.S. patent applicationSer. No. 10/173,547, filed Jun. 14, 2002, and in International PatentApplication No. PCT/US03/18838, filed Jun. 13, 2003.

SimPheny® is a computational system that can be used to produce anetwork model in silico and to simulate the flux of mass, energy orcharge through the chemical reactions of a biological system to define asolution space that contains any and all possible functionalities of thechemical reactions in the system, thereby determining a range of allowedactivities for the biological system. This approach is referred to asconstraints-based modeling because the solution space is defined byconstraints such as the known stoichiometry of the included reactions aswell as reaction thermodynamic and capacity constraints associated withmaximum fluxes through reactions. The space defined by these constraintscan be interrogated to determine the phenotypic capabilities andbehavior of the biological system or of its biochemical components.Analysis methods such as convex analysis, linear programming and thecalculation of extreme pathways as described, for example, in Schillinget al., J. Theor. Biol. 203:229-248 (2000); Schilling et al., Biotech.Bioeng. 71:286-306 (2000) and Schilling et al., Biotech. Prog.15:288-295 (1999), can be used to determine such phenotypiccapabilities.

As described above, one constraints-based method used in thecomputational programs applicable to the invention is flux balanceanalysis. Flux balance analysis is based on flux balancing in a steadystate condition and can be performed as described in, for example, Varmaand Palsson, Biotech. Bioeng. 12:994-998 (1994). Flux balance approacheshave been applied to reaction networks to simulate or predict systemicproperties of, for example, adipocyte metabolism as described in Felland Small, J. Biochem. 138:781-786 (1986), acetate secretion from E.coli under ATP maximization conditions as described in Majewski andDomach, Biotech. Bioeng. 35:732-738 (1990) or ethanol secretion by yeastas described in Vanrolleghem et al., Biotech. Prog. 12:434-448 (1996).Additionally, this approach can be used to predict or simulate thegrowth of E. coli on a variety of single-carbon sources as well as themetabolism of H. influenzae as described in Edwards and Palsson, Proc.Natl. Acad. Sci. 97:5528-5533 (2000), Edwards and Palsson, J. Bio. Chem.274:17410-17416 (1999) and Edwards et al., Nature Biotech. 19:125-130(2001).

Once the solution space has been defined, it can be analyzed todetermine possible solutions under various conditions. Thiscomputational approach is consistent with biological realities becausebiological systems are flexible and can reach the same result in manydifferent ways. Biological systems are designed through evolutionarymechanisms that have been restricted by fundamental constraints that allliving systems must face. Therefore, constraints-based modeling strategyembraces these general realities. Further, the ability to continuouslyimpose further restrictions on a network model via the tightening ofconstraints results in a reduction in the size of the solution space,thereby enhancing the precision with which physiological performance orphenotype can be predicted.

Given the teachings and guidance provided herein, those skilled in theart will be able to apply various computational frameworks for metabolicmodeling and simulation to design and implement growth-coupledproduction of a biochemical product. Such metabolic modeling andsimulation methods include, for example, the computational systemsexemplified above as SimPheny® and OptKnock. For simplicity inillustrating the invention, the methods and strains will be describedherein with reference to the OptKnock computation framework for modelingand simulation. Those skilled in the art will know how to apply theidentification, design and implementation of the metabolic alterationsusing OptKnock to any of such other metabolic modeling and simulationcomputational frameworks and methods well known in the art.

The ability of a cell or organism to obligatory couple growth to theproduction of a biochemical product can be illustrated in the context ofthe biochemical production limits of a typical metabolic networkcalculated using an in silico model. These limits are obtained by fixingthe uptake rate(s) of the limiting substrate(s) to their experimentallymeasured value(s) and calculating the maximum and minimum rates ofbiochemical production at each attainable level of growth. As shown inFIG. 1, the production of a desired biochemical generally is in directcompetition with biomass formation for intracellular resources. Underthese circumstances, enhanced rates of biochemical production willnecessarily result in sub-maximal growth rates. The knockouts suggestedby the above metabolic modeling and simulation programs such as OptKnockare designed to restrict the allowable solution boundaries forcing achange in metabolic behavior from the wild-type strain as depicted inFIG. 1. Although the actual solution boundaries for a given strain willexpand or contract as the substrate uptake rate(s) increase or decrease,each experimental point will lie within its calculated solutionboundary. Plots such as these enable accurate predictions of how closethe designed strains are to their performance limits which alsoindicates how much room is available for improvement.

The OptKnock mathematical framework is exemplified herein forpinpointing gene deletions leading to growth-coupled biochemicalproduction as illustrated in FIG. 1. The procedure builds uponconstraint-based metabolic modeling which narrows the range of possiblephenotypes that a cellular system can display through the successiveimposition of governing physico-chemical constraints, Price et al., NatRev Microbiol, 2: 886-97 (2004). As described above, constraint-basedmodels and simulations are well known in the art and generally invokethe optimization of a particular cellular objective, subject to networkstoichiometry, to suggest a likely flux distribution.

Briefly, the maximization of a cellular objective quantified as anaggregate reaction flux for a steady state metabolic network comprisinga set N={1, . . . , N} of metabolites and a set M={1, . . . , M} ofmetabolic reactions is expressed mathematically as follows:

$\begin{matrix}{maximize} & v_{{cellular}\mspace{14mu}{objective}} & \; \\{{subject}\mspace{20mu}{to}} & {{{\sum\limits_{j = 1}^{M}\;{S_{ij}v_{j}}} = 0},} & {\forall{i \in N}} \\\; & {{v_{substrate} = {v_{substrate\_ uptake}\mspace{11mu}{{{mmol}/{gDW}} \cdot {hr}}}}\mspace{31mu}} & {\forall{i \in \left\{ {{limiting}\mspace{14mu}{substrate}\mspace{14mu}(s)} \right\}}} \\\; & {v_{atp} \geq {v_{{atp\_ main}\mspace{11mu}}{{{mmol}/{gDW}} \cdot {hr}}}} & \; \\\; & {{v_{j} \geq 0},} & {\forall{j \in \left\{ {{irrev}.{reactions}} \right\}}} \\\; & \; & \;\end{matrix}$

where S_(ij) is the stoichiometric coefficient of metabolite i inreaction j, v_(j) is the flux of reaction j, v_(substrate) _(—)_(uptake) represents the assumed or measured uptake rate(s) of thelimiting substrate(s), and v_(atp) _(—) _(main) is the non-growthassociated ATP maintenance requirement. The vector v includes bothinternal and external fluxes. In this study, the cellular objective isoften assumed to be a drain of biosynthetic precursors in the ratiosrequired for biomass formation, Neidhardt, F. C. et al., 2nd ed. 1996,Washington, D.C.: ASM Press. 2 v. (xx, 2822, lxxvi). The fluxes aregenerally reported per 1 gDW·hr (gram of dry weight times hour) suchthat biomass formation is expressed as g biomass produced/gDW·hr or1/hr.

The modeling of gene deletions, and thus reaction elimination, firstemploys the incorporation of binary variables into the constraint-basedapproach framework, Burgard et al., Biotechnol Bioeng, 74: 364-375(2001), Burgard et al., Biotechnol Prog, 17: 791-797 (2001). Thesebinary variables,

$y_{j}\left\{ {\begin{matrix}{1,\mspace{14mu}{{if}\mspace{14mu}{reaction}\mspace{14mu}{flux}\mspace{14mu} v_{j}\mspace{11mu}{is}\mspace{14mu}{active}}} \\{0,\mspace{14mu}{{if}\mspace{14mu}{reaction}\mspace{14mu}{flux}\mspace{14mu} v_{j}\mspace{11mu}{is}\mspace{14mu}{not}\mspace{14mu}{active}}}\end{matrix},{\forall{j \in M}}} \right.$assume a value of 1 if reaction j is active and a value of 0 if it isinactive. The following constraint,v _(j) ^(min) ·y _(j) ≦v _(j) ≦v _(j) ^(max) ·y _(j), ∀ j ε Mensures that reaction flux v_(j) is set to zero only if variable y_(j)is equal to zero. Alternatively, when y_(j) is equal to one, v_(j) isfree to assume any value between a lower v_(j) ^(min) and an upper v_(j)^(max) bound. Here, v_(j) ^(min) and v_(j) ^(max) are identified byminimizing and maximizing, respectively, every reaction flux subject tothe network constraints described above, Mahadevan et al., Metab Eng, 5:264-76 (2003).

Optimal gene/reaction knockouts are identified by solving a bileveloptimization problem that chooses the set of active reactions (y_(j)=1)such that an optimal growth solution for the resulting networkoverproduces the chemical of interest. Schematically, this bileveloptimization problem is illustrated in FIG. 2. Mathematically, thisbilevel optimization problem is expressed as the following bilevelmixed-integer optimization problem:

maximize    v_(chemical               )        (OptKnock)$\mspace{34mu}{y_{i}\begin{pmatrix}\underset{v_{j}}{{subject}\mspace{14mu}{to}} & {maximize} & v_{biomass} & \; \\\; & {{subject}\mspace{14mu}{to}} & {{{\sum\limits_{j = 1}^{M}{S_{ij}v_{j}}} = 0},} & {\forall{i \in N}} \\\; & \; & {v_{substrate} = v_{{substrate}\mspace{14mu}{uptake}}} & {\forall{i \in \left\{ {{limiting}\mspace{20mu}{{substrate}(s)}} \right\}}} \\\; & \; & {v_{atp} \geq v_{atp\_ main}} & \;\end{pmatrix}}$${v_{biomass} \geq {v_{biomass}^{\;{target}}{{v_{j}^{\min} \cdot y_{j}} \leq v_{j} \leq {v_{j}^{\max} \cdot y_{j}}}}},\mspace{14mu}{{\forall{j \in {M{\sum\limits_{j \in M^{forward}}^{\;}\left( {1 - y_{j}} \right)}}}} = {{Ky_{j}} \in \left\{ {0,1} \right\}}},{\forall{j \in M}}$where v_(chemical) is the production of the desired target product, forexample 3-hydroxypropionic acid or other biochemical product, and K isthe number of allowable knockouts. Note that setting K equal to zeroreturns the maximum biomass solution of the complete network, whilesetting K equal to one identifies the single gene/reaction knockout(y_(j)=0) such that the resulting network involves the maximumoverproduction given its maximum biomass yield. The final constraintensures that the resulting network meets a minimum biomass yield.Burgard et al., Biotechnol Bioeng, 84: 647-57 (2003), provide a moredetailed description of the model formulation and solution procedure.Problems containing hundreds of binary variables can be solved in theorder of minutes to hours using CPLEX 8.0, GAMS: The Solver Manuals.2003: GAMS Development Corporation, accessed via the GAMS, Brooke etal., GAMS Development Corporation (1998), modeling environment on an IBMRS6000-270 workstation. The OptKnock framework has already been able toidentify promising gene deletion strategies for biochemicaloverproduction, Burgard et al., Biotechnol Bioeng, 84: 647-57 (2003),Pharkya et al., Biotechnol Bioeng, 84: 887-899 (2003), and establishes asystematic framework that will naturally encompass future improvementsin metabolic and regulatory modeling frameworks.

Any solution of the above described bilevel OptKnock problem willprovide one set of metabolic reactions to disrupt. Elimination of eachreaction within the set or metabolic modification can result in3-hydroxypropionic acid as an obligatory product during the growth phaseof the organism. Because the reactions are known, a solution to thebilevel OptKnock problem also will provide the associated gene or genesencoding one or more enzymes that catalyze each reaction within the setof reactions. Identification of a set of reactions and theircorresponding genes encoding the enzymes participating in each reactionis generally an automated process, accomplished through correlation ofthe reactions with a reaction database having a relationship betweenenzymes and encoding genes.

Once identified, the set of reactions that are to be disrupted in orderto achieve growth-coupled 3-hydroxypropionic acid production areimplemented in the target cell or organism by functional disruption ofat least one gene encoding each metabolic reaction within the set. Asdescribed previously, one particularly useful means to achievefunctional disruption of the reaction set is by deletion of eachencoding gene. However, in some instances, it can be beneficial todisrupt the reaction by other genetic aberrations including, forexample, mutation, deletion of regulatory regions such as promoters orcis binding sites for regulatory factors, or by truncation of the codingsequence at any of a number of locations. These latter aberrations,resulting in less than total deletion of the gene set can be useful, forexample, when rapid assessments of the product coupling are desired orwhen genetic reversion is less likely to occur.

To identify additional productive solutions to the above describedbilevel OptKnock problem which lead to further sets of reactions todisrupt or metabolic modifications that can result in the growth-coupledproduction of 3-hydroxypropionic acid or other biochemical products, anoptimization method, termed integer cuts, can be implemented. Thismethod proceeds by iteratively solving the OptKnock problem exemplifiedabove with the incorporation of an additional constraint referred to asan integer cut at each iteration. Integer cut constraints effectivelyprevent the solution procedure from choosing the exact same set ofreactions identified in any previous iteration that obligatory couplesproduct biosynthesis to growth. For example, if a previously identifiedgrowth-coupled metabolic modification specifies reactions 1, 2, and 3for disruption, then the following constraint prevents the samereactions from being simultaneously considered in subsequent solutions:y₁+y₂+y₃≧1. The integer cut method is well known in the art and can befound described in, for example, reference, Burgard et al., BiotechnolProg, 17: 791-797 (2001). As with all methods described herein withreference to their use in combination with the OptKnock computationalframework for metabolic modeling and simulation, the integer cut methodof reducing redundancy in iterative computational analysis also can beapplied with other computational frameworks well known in the artincluding, for example, SimPheny.

Constraints of the above form preclude identification of larger reactionsets that include previously identified sets. For example, employing theinteger cut optimization method above in a further iteration wouldpreclude identifying a quadruple reaction set that specified reactions1, 2, and 3 for disruption since these reactions had been previouslyidentified. To ensure identification of all possible reaction setsleading to growth-coupled production of a product, a modification of theinteger cut method was employed.

Briefly, the modified integer cut procedure begins with iteration ‘zero’which calculates the maximum production of the desired biochemical atoptimal growth for a wild-type network. This calculation corresponds toan OptKnock solution with K equaling 0. Next, single knockouts areconsidered and the two parameter sets, objstore_(iter) andystore_(iter,j), are introduced to store the objective function(v_(chemical)) and reaction on-off information (y_(j)), respectively, ateach iteration, iter. The following constraints are then successivelyadded to the OptKnock formulation at each iteration.v _(chemical)≧objstore_(iter) +ε−M·Σ _(jεystore) _(iter,j) ₌₀ y _(j)

In the above equation, ε and M are a small and a large numbers,respectively. In general, ε can be set at about 0.01 and M can be set atabout 1000. However, numbers smaller and/or larger then these numbersalso can be used. M ensures that the constraint can be binding only forpreviously identified knockout strategies, while censures that addingknockouts to a previously identified strategy must lead to an increaseof at least ε in biochemical production at optimal growth. The approachmoves onto double deletions whenever a single deletion strategy fails toimprove upon the wild-type strain. Triple deletions are then consideredwhen no double deletion strategy improves upon the wild-type strain, andso on. The end result is a ranked list, represented as desiredbiochemical production at optimal growth, of distinct deletionstrategies that differ from each other by at least one knockout. Thisoptimization procedure as well as the identification of a wide varietyof reaction sets that, when disrupted, lead to the growth-coupledproduction of a biochemical product are exemplified in detail furtherbelow in the Examples. The Examples further exemplify the growth-coupledproduction of 3-hydroxypropionic acid. However, given the teachings andguidance provided herein, those skilled in the art will understand thatthe methods and metabolic engineering designs exemplified herein areequally applicable to the obligatory coupling of cell or microorganismgrowth to any biochemical product.

Biochemical synthesis of 3-HP has been established, and several routescan be found in the propanoate metabolism map in the KEGG pathwaydatabase shown in FIG. 3 and found at the URLgenome.jp/dbget-bin/show-pathway?map00640. However, complete pathwaysare not present in certain industrial microbes such as E. coli or S.cerevisiae. One useful E. coli well known in the art can produce 3-HP byfermentation via lactic acid is a strain recombinantly expressinglactyl-CoA dehydratase and 3-hydroxypropionyl-CoA dehydratase. Thisstrain is described in U.S. Patent Application 20040076982. A moreenergetically favorable route is the synthesis of 3-HP from malonicsemialdehyde, via the intermediate β-alanine. However, the synthesisroute for β-alanine is extensive and has the same energetic barrier asthe lactic pathway. A further alternative well known in the art isthrough expression of a 2,3-aminomutase enzyme which converts L-alanineto β-alanine. Expression of this aminomutase creates a pathway frompyruvate to 3-HP in 4 biochemical steps and is described in U.S. PatentApplication 20050221466) A 2-step recombinant pathway for creating 3-HPproducing microorganisms from glycerol is described in U.S. Pat. No.6,852,517.

These and other microorganisms known in the art expressing 3-HP orengineered to express 3-HP can be employed in the methods of theinvention or used to derive the non-naturally occurring microorganismsof the invention. Similarly, microorganisms other than E. coli also canbe recombinantly engineered to contain substantially the same or similarexogenous pathways so as to express 3-HP for use in the methods of theinvention or for deriving a non-naturally occurring microorganism of theinvention. Further, in addition to the engineered pathways exemplifiedin the above publications, any of a variety of other metabolicalternatives can be recombinantly engineered into a microorganism ofchoice to convert a non-producing 3-HP microorganism into a 3-HPproducing microorganism. Such other metabolic alternatives include, forexample, introducing metabolic pathways that produce any of the 3-HPprecursors shown in FIG. 3. Exemplary metabolic alternatives include,for example, engineering exogenous pathways for β-alanine, malonyl-CoAand lactoyl-CoA shown in FIGS. 3 and 4 to produce malonate semialdehyde,malonate semialdehyde and 3-hydroxypropanoyl-CoA, respectively, in amicroorganism that produces little, if any, of these 3-HP precursors.

Employing the methods exemplified above and further illustrated in theExamples below, the methods of the invention enable the construction ofcells and organisms that obligatory couple the production of a targetbiochemical product to growth of the cell or organism engineered toharbor the identified genetic alterations. In this regard, metabolicalterations have been identified that obligatory couple the productionof 3-HP to microorganism growth. Microorganism or microbial strainsconstructed with the identified metabolic alterations produce elevatedlevels of 3-HP during the exponential growth phase. These strains can bebeneficially used for the commercial production of 3-HP in continuousfermentation process without being subjected to the negative selectivepressures described previously.

Therefore, the methods of the invention provide a set of metabolicmodifications that are identified by an in silico method selected fromOptKnock or SimPheny. The set of metabolic modifications can includefunctional disruption of one or more metabolic reactions including, forexample, disruption by gene deletion. The metabolic modifications can beselected from the set of metabolic modifications listed in Table 2.

Also provided is a method of producing a non-naturally occurringmicroorganism having stable growth-coupled production of 3-HP. Themethod includes: (a) identifying in silico a set of metabolicmodifications requiring 3-HP production during exponential growth; (b)genetically modifying a microorganism to contain the set of metabolicmodifications requiring 3-HP production, and culturing the geneticallymodified microorganism. Culturing can include adaptively evolving thegenetically modified microorganism under conditions requiring 3-HPproduction. The methods of the invention are applicable to bacterium,yeast and fungus as well as a variety of other cells and microorganism.The bacteria can include, for example, E. coli, A. succiniciproducens,A. succinogenes, M. succiniciproducens, R. etli, Bacillus subtilis,Corynebacterium glutamicum, Gluconobacter oxydans, Zymomonas mobilis,Lactococcus lactis, Lactobacillus plantarum, Streptomyces coelicolor,Clostridium acetobutylicum, Pseudomonas fluorescens Klebsiella oxytocaand Pseudomonas putida. Yeast can include, for example, Saccharomycescerevisiae, Schizosaccharomyces pombe, Kluyveromyces lactis,Kluyveromyces marxianus, Penicilium chrysogenum, Aspergillus terreus,Aspergillus niger and Pichia pastoris.

A microorganism produced by the methods of the invention is furtherprovided. Therefore, the invention provides non-naturally occurringmicroorganism having one or more gene disruptions occurring in genesencoding an enzyme obligatory coupling 3-hydroxypropionic acidproduction to growth of the microorganism when the gene disruptionreduces an activity of said enzyme, whereby the one or more genedisruptions confers stable growth-coupled production of3-hydroxypropionic acid onto the non-naturally occurring microorganism.

The non-naturally occurring microorganism can have one or more genedisruptions included in a metabolic modification listed in Table 2. Theone or more gene disruptions can be a deletion. The non-naturallyoccurring microorganism of the invention can be selected from the groupof microorganisms having a metabolic modification listed in Table 2.Specific examples of the non-naturally occurring microorganisms of theinvention are set forth below in Example I. Non-naturally occurringmicroorganisms of the invention include bacteria, yeast, fungus or anyof a variety of other microorganisms applicable to fermentationprocesses. Exemplary bacteria include species selected from E. coli, A.succiniciproducens, A. succinogenes, M. succiniciproducens, R. etli,Bacillus subtilis, Corynebacterium glutamicum, Gluconobacter oxydans,Zymomonas mobilis, Lactococcus lactis, Lactobacillus plantarum,Streptomyces coelicolor, Clostridium acetobutylicum, Pseudomonasfluorescens, Klebsiella oxytoca and Pseudomonas putida. Exemplary yeastsinclude species selected from Saccharomyces cerevisiae,Schizosaccharomyces pombe, Kluyveromyces lactis, Kluyveromycesmarxianus, Penicilium chrysogenum, Aspergillus terreus, Aspergillusniger and Pichia pastoris.

The microorganisms having growth-coupled 3-HP production are exemplifiedherein with reference to an E. coli genetic background. However, withthe complete genome sequence available for now more than 550 species(with more than half of these available on public databases such as theNCBI), including 395 microorganism genomes and a variety of yeast,fungi, plant, and mammalian genomes, the identification of an alternatespecies homolog for one or more genes, including for example, orthologs,paralogs and nonorthologous gene displacements, and the interchange ofgenetic alterations between organisms is routine and well known in theart. Accordingly, the metabolic alterations enabling growth-coupledproduction of 3-HP described herein with reference to a particularorganism such as E. coli can be readily applied to other microorganisms,including prokaryotic and eukaryotic organisms alike. Given theteachings and guidance provided herein, those skilled in the art willknow that a metabolic alteration exemplified in one organism can beapplied equally to other organisms.

For example, 3-HP production can be coupled to exponential growth in E.coli by deletion or functional removal of one or more genes encodingenzymes catalyzing the reaction referred to herein as LDH_D. As shown inTable 2, there are two E. coli genes that encode an enzyme catalyzingthe LDH_D reaction. These two LDH_D associated genes are ldhA and dld.The common name for the enzyme encoding the LDH_D reaction is ldhA. Thedld gene is an ortholog of ldhA. To produce a metabolically engineeredE. coli exhibiting growth coupled 3-HP production employing diminutionor removal of the LDH_D reaction, a gene encoding at least one enzymecatalyzing the LDH_D reaction has to be functionally disrupted. Such adisruption can occur, for example, by deleting either or both of theldhA gene and/or its ortholog did. For the growth-coupled production of3-HP employing diminution or removal of the LDH_D reaction in a cell ororganism other then E. coli, the genes encoding the comparable reactionor the comparable reactions for LDH_D in the species of interest can befunctionally disrupted. For those organisms having analogous metabolicpathways such disruption can be accomplished by deleting, for example,the species homologue to either or both of the ldhA and/or dld genes. Asdescribed previously, such homologues can include othologs and/ornonorthologous gene displacements. In some instances, such as when asubstitute metabolic pathway exists in the species of interest,functional disruption can be accomplished by, for example, deletion of aparalog that catalyzes a similar, yet non-identical metabolic reactionwhich replaces the referenced reaction. Because certain differencesexist among metabolic networks between different organisms, thoseskilled in the art will understand that the actual genes disruptedbetween different organisms may differ. However, the given the teachingsand guidance provided herein, those skilled in the art also willunderstand that the methods of the invention can be applied to allmicroorganisms to identify the cognate metabolic alterations betweenorganisms and to construct an organism in a species of interest thatwill enhance the coupling of 3-HP biosynthesis to growth.

The invention will be described herein with general reference to themetabolic reaction, reactant or product thereof, or with specificreference to one or more genes associated with the referenced metabolicreaction, reactant or product. Unless otherwise expressly stated herein,those skilled in the art will understand that reference to a reactionalso constitutes reference to the reactants and products of thereaction. Similarly, unless otherwise expressly stated herein, referenceto a reactant or product also references the reaction and that referenceto any of these metabolic constitutes also references the gene or genesencoding the enzymes that catalyze the referenced reaction, reactant orproduct. Likewise, given the well known fields of metabolicbiochemistry, enzymology and genomics, reference herein to a gene alsoconstitutes a reference to the corresponding encoded enzyme and thereaction it catalyzes as well as the reactants and products of thereaction. As described previously and further below, exemplaryreactions, reaction nomenclature, reactants, products, cofactors andgenes encoding enzymes catalyzing a reaction involved in thegrowth-coupled production of 3-HP are set forth in Tables 1, 2 and 3.

The invention provides microorganisms having growth-coupled productionof 3-HP. 3-HP production is obligatory linked to the exponential growthphase of the microorganism by genetically altering the metabolicpathways of the cell. The genetic alterations make 3-HP an obligatoryproduct during the growth phase. Sets of metabolic alterations ortransformations that result in elevated levels of 3-HP biosynthesisduring exponential growth are exemplified in Table 2. Each alterationwithin a set corresponds to the requisite metabolic reaction that shouldbe functionally disrupted. Functional disruption of all reactions withineach set results in the obligatory production of 3-HP by the engineeredstrain during the growth phase. The corresponding reactions to thereferenced alterations in and the gene or genes that encode them in E.coli, are set forth in Table 2. Table 3 provides the full biochemicalnames for the reactants, cofactors and products referenced in thereactions of Table 2.

The host microorganism can be selected to produce 3-HP precursors and/or3-HP. Alternatively, non-3-HP producing microorganisms can begenetically modified to produce 3-HP or any required 3-HP precursorsneeded for the microorganism to complete biosynthesis of 3-HP. Specificexamples of microorganisms genetically modified to produce 3-HP arethose described above in, for example, U.S. Patent Application Nos.20040076982 20050221466, and in U.S. Pat. No. 6,852,517, and furtherexemplified in Example I. The overall conversion stoichiometry ofvarious pathways to 3-HP for such exemplary microorganisms geneticallymodified to produce 3-HP is shown in Table 1.

For example, for each strain containing disruption of one or morereactions set forth in Table 2 or for each strain exemplified in ExampleI, the metabolic alterations that can be generated for growth coupled3-HP production are shown in each row. These alterations include thefunctional disruption of from one to five or more reactions. Inparticular, 20 strains are exemplified in Example I that havenon-naturally occurring metabolic genotypes. Each of these non-naturallyoccurring alterations result in an enhanced level of 3-HP productionduring the exponential growth phase of the microorganism compared to awild-type strain, under appropriate culture conditions. Appropriateconditions include, for example, those exemplified further below in theExamples such as particular carbon sources or reactant availabilitiesand/or adaptive evolution.

Given the teachings and guidance provided herein, those skilled in theart will understand that to disrupt an enzymatic reaction it isnecessary to disrupt the catalytic activity of the one or more enzymesinvolved in the reaction. Disruption can occur by a variety of meansincluding, for example, deletion of an encoding gene or incorporation ofa genetic alteration in one or more of the encoding gene sequences. Theencoding genes targeted for disruption can be one, some, or all of thegenes encoding enzymes involved in the catalytic activity. For example,where a single enzyme is involved in a targeted catalytic activitydisruption can occur by a genetic alteration that reduces or destroysthe catalytic activity of the encoded gene product. Similarly, where thesingle enzyme is multimeric, including heteromeric, disruption can occurby a genetic alteration that reduces or destroys the function of one orall subunits of the encoded gene products. Destruction of activity canbe accomplished by loss of the binding activity of one or more subunitsin order to form an active complex, by destruction of the catalyticsubunit of the multimeric complex or by both. Other functions ofmultimeric protein association and activity also can be targeted inorder to disrupt a metabolic reaction of the invention. Such otherfunctions are well known to those skilled in the art. Further, some orall of the functions of a single polypeptide or multimeric complex canbe disrupted according to the invention in order to reduce or abolishthe catalytic activity of one or more enzymes involved in a reaction ormetabolic modification of the invention. Similarly, some or all ofenzymes involved in a reaction or metabolic modification of theinvention can be disrupted so long as the targeted reaction isdestroyed.

Given the teachings and guidance provided herein, those skilled in theart also will understand that an enzymatic reaction can be disrupted byreducing or eliminating reactions encoded by a common gene and/or by oneor more orthologs of that gene exhibiting similar or substantially thesame activity. Reduction of both the common gene and all orthologs canlead to complete abolishment of any catalytic activity of a targetedreaction. However, disruption of either the common gene or one or moreorthologs can lead to a reduction in the catalytic activity of thetargeted reaction sufficient to promote coupling of growth to 3-HPbiosynthesis. Exemplified herein are both the common genes encodingcatalytic activities for a variety of metabolic modifications as well astheir orthologs. Those skilled in the art will understand thatdisruption of some or all of the genes encoding a enzyme of a targetedmetabolic reaction can be practiced in the methods of the invention andincorporated into the non-naturally occurring microorganisms of theinvention in order to achieve the growth-coupled 3-HP production.

Therefore, the invention further provides a non-naturally occurringmicroorganism having a set of metabolic modifications obligatorycoupling 3-hydroxypropionic acid production to growth of saidmicroorganism, said set of metabolic modifications comprising disruptionof one or more genes comprising:

(a) the set of genes selected from: (1) adhE, ldhA, pta-ackA; (2) adhE,ldhA, frdABCD; (3) adhE, ldhA, frdABCD, ptsG; (4) adhE, ldhA, frdABCD,pntAB; (5) adhE, ldhA, fumA, fumB, fumC; (6) adhE, ldhA, fumA, fumB,fumC, pntAB; (7) pflAB, ldhA, or (8) adhE, ldhA, pgi in a microorganismutilizing an anaerobic β-alanine 3-HP precursor pathway;

(b) the set of genes selected from: (1) tpi, zwf; (2) tpi, ybhE; (3)tpi, gnd; (4) fpb, gapA; (5) pgi, edd, or (6) pgi, eda in amicroorganism utilizing an aerobic glycerol 3-HP precursor pathway;

(c) the set of genes selected from: (1) eno; (2) yibO; (3) eno, atpH, orother atp subunit, or (4) yibO, atpH, or other atp subunit, in amicroorganism utilizing a glycerate 3-HP precursor pathway,

or an ortholog thereof, wherein said microorganism exhibits stablegrowth-coupled production of 3-hydroxypropionic acid.

The common names for the genes encoding the enzymes responsible forcatalyzing the specified reactions are shown in parenthesis in Table 2and in the exemplary strains described further below in Example I. Thenon-naturally occurring microorganism having genes encoding themetabolic modification (a)(7) pflAB, ldhA can further include disruptionof at least one gene selected from aceEF, ptsG or frdABCD. Thenon-naturally occurring microorganism having genes encoding themetabolic modification (a)(8) adhE, ldhA, pgi can further includedisruption of at least one gene selected from glk orfrdABCD. Thenon-naturally occurring microorganism having genes encoding themetabolic modification (b)(1) tpi, zwf, (b)(2) tpi, ybhE or (b)(3) tpi,gnd can further include disruption of at least one gene selected fromzwf, adhC, gcd, mgsA, or deoC. The non-naturally occurring microorganismgenes encoding the metabolic modification (b)(4) fpb, gapA can furtherinclude disruption of at least one gene selected from glpX, gapC, adhC,mgsA, fsa, talC or gcd. The non-naturally occurring microorganism havinggenes encoding the metabolic modification (b)(5) pgi, edd or (b)(6) pgi,eda can further include disruption of at least one gene selected fromadhC, gcd or deoC. The non-naturally occurring microorganism havinggenes encoding the metabolic modification (c)(1) eno or (c)(2) yibO canfurther include disruption of at least both genes eno and yibO. Thenon-naturally occurring microorganism having genes encoding themetabolic modification (c)(3) eno, atpH, or other atp subunit, or (c)(4)yibO, atpH, or other atp subunit, can further include disruption of atleast one gene selected from atpABCDEFGHI, aceEF, pflA, pflB, sucCD orsucAB, pta-ackA.

Briefly, with respect to the genes exemplified above and theirrelationship to their cognate subunits within multimeric complexes,their orthologs and the reactions catalyzed by their gene products,ADHEr is catalyzed by the enzyme encoded by one gene, b1241 (adhE).LDH_D is encoded by the product of one gene, b1380 (ldhA), which has anortholog b2133 (dld). PFL activity requires enzyme subunits encoded bytwo genes, b0902 and 0903, (represented collectively as pflAB). b3114(tdcE) is an ortholog to b0903 (pflB). PTAr is encoded by the product ofone gene, b2297 (pta). This gene is typically removed along with theadjacent gene, b2296 (ackA), to help eliminate acetate production fromacetyl coenzyme-A. FUM is encoded by the product of three differentorthologous genes: b1612 (fumA), b4122 (fumB), and b1611 (fumC). FRDactivity requires enzyme subunits encoded by four genes, b4151, b4152,b4153, and b4154 (represented collectively as frdABCD). If expressed,the genes b0721, b0722, b0723, b0724 (represented collectively assdhABCD) can also impart FRD activity. ATPS4r is catalyzed by amultisubunit enzyme encoded by the nine genes b3731-b3739, which arerepresented collectively as atpABCDEFGHI. GLCpts activity requiresenzyme subunits encoded by nine genes: b2415, b2416, b2417, b1817,b1818, b1819, b1101, b0679, and b1621 (represented collectively asptsG). AKGD activity requires both b0726 and b0727 (representedcollectively as sucAB). PDH activity requires both b0114 and b0115(represented collectively as aceEF). SUCOAS activity requires both b0728and b0729 (represented collectively as sucCD). THD2 activity requiresboth b1602 and b1603 (represented collectively as pntAB). Since thereactions ATPS4r, FRD, PFL, GLCpts, AKGD, PDH, SUCOAS, and THD2 arecarried out by protein complexes encoded by multiple genes, deleting oneor a combination of genes from the atp, frd, pfl, pts, suc(A or B), ace,suc(C or D), or pnt gene clusters, respectively, are thus sufficient fordisrupting the reactions. In the remaining cases, the gene responsiblefor the primary reaction activity in E. coli was chosen, based oninformation in the literature.

The non-naturally occurring microorganisms of the invention can beemployed in the growth-coupled production of 3-HP. Essentially anyquantity, including commercial quantities, can be synthesized using thegrowth-coupled 3-HP producers of the invention. Because themicroorganisms of the invention obligatory couple 3-HP to growthcontinuous or near-continuous growth processes are particularly usefulfor biosynthetic production of 3-HP. Such continuous and/or nearcontinuous growth processes are described above and exemplified below inthe Examples. Continuous and/or near-continuous microorganism growthprocess also are well known in the art. Briefly, continuous and/ornear-continuous growth processes involve maintaining the microorganismin an exponential growth or logarithmic phase. Procedures include usingapparatuses such as the Evolugator™ evolution machine (Evolugate LLC,Gainesville, Fla.), fermentors and the like. Additionally, shake flaskfermentation and growth under microaerobic conditions also can beemployed. Given the teachings and guidance provided herein those skilledin the art will understand that the growth-coupled 3-HP producingmicroorganisms can be employed in a variety of different settings undera variety of different conditions using a variety of different processesand/or apparatuses well known in the art.

Generally, the continuous and/or near-continuous production of 3-HP willinclude culturing a non-naturally occurring growth-coupled 3-HPproducing organism of the invention in sufficient nutrients and mediumto sustain and/or nearly sustain growth in an exponential phase.Continuous culture under such conditions can include, for example, aday, 2, 3, 4, 5, 6 or 7 days or more. Additionally, continuous culturecan include 1 week, 2, 3, 4 or 5 or more weeks and up to several months.In is to be understood that the continuous and/or near-continuousculture conditions also can include all time intervals in between theseexemplary periods.

3-HP can be harvested or isolated at any time point during thecontinuous and/or near-continuous culture period exemplified above. Asexemplified below in the Examples, the longer the microorganisms aremaintained in a continuous and/or near-continuous growth phase, theproportionally greater amount of 3-HP can be produced.

Therefore, the invention provides a method of producing3-hydroxypropionic acid coupled to the growth of a microorganism. Themethod includes: (a) culturing under exponential growth phase in asufficient amount of nutrients and media a non-naturally occurringmicroorganism comprising a set of metabolic modifications obligatorycoupling 3-hydroxypropionic acid production to growth of saidmicroorganism, said set of metabolic modifications comprising disruptionof one or more genes comprising:

(1) the set of genes selected from: (a) adhE, ldhA, pta-ackA; (b) adhE,ldhA, frdABCD; (c) adhE, ldhA, frdABCD, ptsG; (d) adhE, ldhA, frdABCD,pntAB; (e) adhE, ldhA, fumA, fumB, fumC; (f) adhE, ldhA, fumA, fumB,fumC, pntAB; (g) pflAB, ldhA, or (h) adhE, ldhA, pgi in a microorganismutilizing an anaerobic β-alanine 3-HP precursor pathway;

(2) the set of genes selected from: (a) tpi, zwf; (b) tpi, ybhE; (c)tpi, gnd; (d) fpb, gapA; (e) pgi, edd, or (f) pgi, eda in amicroorganism utilizing an aerobic glycerol 3-HP precursor pathway;

(3) the set of genes selected from: (a) eno; (b) yibO; (c) eno, atpH, orother atp subunit, or (d) yibO, atpH, or other atp subunit, in amicroorganism utilizing a glycerate 3-HP precursor pathway,

or an ortholog thereof, wherein said microorganism exhibits stablegrowth-coupled production of 3-hydroxypropionic acid, and

(b) isolating 3-hydroxypropionic acid produced from said non-naturallyoccurring microorganism.

The genes encoding the metabolic modification (a)(1)(g) pflAB, ldhA canfurther include disruption of at least one gene selected from aceEF,ptsG or frdABCD. The genes encoding the metabolic modification (a)(1)(h)adhE, ldhA, pgi can further include disruption of at least one geneselected from glk orfrdABCD. The genes encoding said metabolicmodification (a)(2)(a) tpi, zwf, (a)(2)(b) tpi, ybhE or (a)(2)(c) tpi,gnd can further include disruption of at least one gene selected fromzwf, adhC, gcd, mgsA, or deoC. The genes encoding the metabolicmodification (a)(2)(d) fpb, gapA can further include disruption of atleast one gene selected from glpX, gapC, adhC, mgsA, fsa, talC or gcd.The genes encoding said metabolic modification (a)(2)(e) pgi, edd or(a)(2)(f) pgi, eda can further include disruption of at least one geneselected from adhC, gcd or deoC. The genes encoding said metabolicmodification (a)(3)(a) eno or (a)(3)(b) yibO can further includedisruption of at least both genes eno and yibO. The genes encoding saidmetabolic modification (a)(3)(c) eno, atpH, or other atp subunit, or(a)(3)(d) yibO, atpH, or other atp subunit, can further includedisruption of at least one gene selected from atpABCDEFGHI, aceEF, pflA,pflB, sucCD or sucAB, pta-ackA.

It is understood that modifications which do not substantially affectthe activity of the various embodiments of this invention are alsoincluded within the definition of the invention provided herein.Accordingly, the following examples are intended to illustrate but notlimit the present invention.

EXAMPLE I Microorganisms Having Growth-Coupled Production of3-Hydroxypropionic Acid

In this Example, the metabolic engineering strategies identified by themethods described previously are described. Overall, several hundredplausible strategies were identified. A summary of the conversionstoichiometry of several 3-HP pathways can be found in Table 1 below.Table 2 sets forth a listing of E. coli genes responsible for catalyzingreactions targeted for removal whereas Table 3 provides thecorresponding metabolic abbreviations. Table 4 provides the Blattnernumbers corresponding to the genes listed in Table 2.

Briefly, particularly useful designs for the purpose of demonstratingthe methods described herein were placed into three categories: (1)removal of competing fermentation pathways, (2) elimination of pyruvateconsuming reactions, and (3) alternative strategies. The solutionboundaries for each design are obtained by separately maximizing andminimizing 3-HP production at every feasible growth rate. Evolutionaryengineering can be employed to drive the performance of the variousstrains towards the rightmost portion of every solution boundary. Thiscorresponds to the “optimal growth” solution or the maximum biomassyield. Completely anaerobic conditions are assumed along with a basisglucose uptake rate of 10 mmol/gDW/hr. Characterization of exemplarystrains within each of the above categories are described further below.Procedures for the construction and culturing of strains identified ashaving growth-coupled 3-hydroxypropionic acid production also aredescribed further below.

Knockout design strategies for producing 3-hydroxypropionic acid in ametabolic network are described further below. The strategies weredetermined by employing a genome-scale model of the E. coli metabolicnetwork. The solution of the bilevel OptKnock problem provides one setof deletions. To enumerate further meaningful solutions (i.e., all setsof knockouts leading to growth-coupled production formation), anoptimization technique, termed integer cuts, can be implemented. Asdescribed previously, this method proceeds by iteratively solving theOptKnock problem with the incorporation of an additional constraintreferred to as an integer cut at each iteration.

Set forth below are exemplary identified designs for increasing 3-HPproduction in E. coli. A preliminary evaluation of more than 100 aerobicand anaerobic knockout strategies predicted by employing the reduced E.coli metabolic network was undertaken first. A representative subset ofthese evaluated designs was further characterized for their effect onthe complete model of E. coli comprised of 1,145 reactions. 3-HP wasselected to be secreted via proton symport. The solution goal for thefinal selection of designs was a growth-coupled yield of 3-HP. Toexamine this characteristic, production cones were constructed for eachstrategy by first maximizing and subsequently, minimizing the 3-HPyields at different rates of biomass formation feasible in the network.Adaptive evolutionary engineering strategies can be employed to drivethe performance of the various strains towards the rightmost portion ofevery solution boundary. If the rightmost boundary of all possiblephenotypes of an altered network is a single point, this resultindicates that there is a unique optimum yield of 3-HP at the maximumbiomass formation rate possible in the network. The 3-HP and biomassyields are reported for a basis glucose uptake rate of 10 mmol/gDW·hr.

Maximum Yields of Metabolic Pathways to 3-HP:

In this report, we summarize metabolic engineering designs undersimulated conditions where 3-HP is produced by (i) an anaerobic routethrough β-alanine; (ii) an aerobic route through glycerol, or (iii) anin silico designed pathway through glycerate.

For the anaerobic β-alanine route, the following reactions wereavailable to the E. coli metabolic network:

Pyruvate/alanine aminotransferase:pyruvate+L-glutamate→L-alanine+alpha-ketoglutarate

Alanine-2,3-aminotransferase: L-alanine→β-alanine

β-alanine aminotransferase: β-alanine+alpha-ketoglutarate→malonatesemialdehyde+L-glutamate

3-hydroxypropionic acid dehydrogenase: malonatesemialdehyde+NADH+H→3-hydroxypropionic acid+NAD

The designs exemplified herein resulting from the above pathways areapplicable if any conceivable sequence of reactions is present in E.coli metabolic model that can lead to the net conversion of one moleculeof pyruvate to one molecule of 3-HP with the simultaneous regenerationof 1 molecule of NAD (or NADP) from NADH (or NADPH).

For the production pathway through glycerol, the following non-nativereactions were available to the E. coli metabolic network:

Glycerol dehydratase: Glycerol→3-Hydroxypropanal+H2O

Aldehyde dehydrogenase: 3-hydroxypropanal+H2O+NAD→3-hydroxypropionicacid+2H+NADH

The designs exemplified herein resulting from the above pathways areapplicable if any conceivable sequence of reactions is present in themetabolic model that can lead to the net conversion of one molecule ofglycerol to one molecule of 3-HP with the simultaneous generation of 1molecule of NADH(NADPH) from NAD (NADP).

The glycerate pathway relies on the following reactions to be available:

3-phosphoglycerate phosphatase: 3-phosphoglycerate+H₂O→glycerate+Pi

Glycerate dehydratase: glycerate→H₂O+malonate semialdehyde

3-hydroxypropionic acid dehydrogenase: malonatesemialdehyde+NADH+H→3-hydroxypropionic acid+NAD

If, in vivo, the E. coli glycerate kinase can be used to form glycerate,then this reaction is preferentially used over 3-phosphoglyceratephosphatase, which does not lead to the generation of an ATP molecule.The designs exemplified herein resulting from the above pathways areapplicable if any conceivable sequence of reactions is present in themetabolic model that can lead to the net conversion of one molecule of3-phosphoglycerate to one molecule of 3-HP with the simultaneousgeneration of 1 molecule of NADH (NADPH) from NAD (NADP). FIG. 4illustrates the above production routes along with a several otherroutes well known in the art and described in U.S. Pat. No. 6,852,517and in U.S. Patent Application 2004/0076982 A1.

The maximum theoretical yields of the above pathways are illustrated inFIG. 4 and shown below in Table 1. These yields assume for simulationpurposes either no energetic requirement or that the production of eachmol of 3-HP is accompanied by the production of 1 mol of ATP. Pathwaysare labeled as aerobic if they fail to generate enough ATP to operate atdesired levels and are forced to rely on some degree of oxygenation forenergy generation. Pathways with higher oxygen requirements are lessenergetically efficient.

TABLE 1 The overall conversion stoichiometry of various pathways to 3-HPassuming (A) no additional energetic requirement and (B) an energeticrequirement of 1 ATP per 3-HP produced. Glucose and oxygen are taken upwhile all other molecules are produced. (A) β-alanine (L-ala) β-alanine(L-asp) Glycerol Glycerate* Glycerate** Lactate Malonyl-CoA AnaerobicAerobic Aerobic Anaerobic Aerobic Anaerobic Aerobic Glucose 1.000 1.0001.000 1.000 1.000 1.000 1.000 Oxygen 0.000 0.071 0.722 0.000 0.072 0.0000.240 Protons 2.000 1.976 1.759 2.000 1.976 2.000 1.920 3HP 2.000 1.9761.759 2.000 1.976 2.000 1.920 CO2 0.000 0.071 0.722 0.000 0.072 0.0000.240 H2O 0.000 0.071 0.722 0.000 0.072 0.000 0.240 (B) β-alanine(L-ala) β-alanine (L-asp) Glycerol Glycerate* Glycerate** LactateMalonyl-CoA Anaerobic Aerobic Aerobic Aerobic Aerobic Anaerobic AerobicGlucose 1.000 1.000 1.000 1.000 1.000 1.000 1.000 Oxygen 0.000 0.5811.114 0.072 0.593 0.000 0.667 Protons 2.000 1.810 1.629 1.976 1.8022.000 1.778 3HP 2.000 1.810 1.629 1.976 1.802 2.000 1.778 CO2 0.0000.581 1.114 0.072 0.593 0.000 0.667 H2O 0.000 0.581 1.114 0.072 0.5930.000 0.667 ATP 2.000 1.810 1.629 1.976 1.802 2.000 1.778 *assumesglycerate is generated by glycerate kinase (i.e., 3pg + adp → atp +glycerate) **assumes glycerate is generated by 3-phosphoglyceratephosphatase as shown in FIG. 4 (3pg + h₂o → Pi + glycerate)

OptKnock-derived Knockout Designs:

Briefly, OptKnock was employed as described previously to identifyreactions to be eliminated from an in silico model organism to couplethe biochemical production and biomass yields. The identified designsexemplified herein list the metabolic reactions targeted for removal byOptKnock. The E. coli genes known to encode the enzymes that catalyzeeach reaction also are provided to describe which genetic modificationscan be implemented to achieve the growth-coupled production phenotypesidentified by the in silico methods of the invention. Given theteachings and guidance provided herein, those skilled in the art willunderstand that if new discoveries reveal further genes in the modelorganism's genome that can confer one or more of the reactionsfunctionalities targeted for removal in a given design, then those genesalso can be removed to further augment growth-coupled production of 3-HPfor the stains identified by the methods the invention and for thoserepresentative strains exemplified herein.

In certain growth-coupled 3-HP producing strains of the invention, itcan be sufficient to reduce or prevent the activity of a subset of thereactions in each of the growth-coupled 3-HP producing designs tomaintain or confer a growth-coupled producing phenotype. The subset caninclude inhibiting at least one, some or one less than all of theidentified activities within the set. For example, if an identifieddesign specifies removal of a particular reaction whose activity in vivois insufficient to uncouple growth from 3-HP production, then the genesencoding the enzymes that catalyze this reaction can be left in tact. Inaddition, any combination (i.e., at least one and at most all) of thelisted gene deletions for a given reaction can have the desired effectof ensuring that reaction is non-functional in E. coli or another modelorganism. For convenience, the designs exemplified herein are providedin the following format:

-   -   design #) genes targeted for removal (abbreviations of reactions        targeted for removal).

Table 2 contains a list of reactions targeted for removal for theexemplified growth-coupled 3-HP producing strains along with theirabbreviations, genes and stoichiometry. Methods for constructing strainsthat remove or inhibit these exemplary reactions targeted for removal ina given design are well known to those skilled in the art

TABLE 2 Known E. coli genes responsible for catalyzing the reactionstargeted for removal. Metabolite abbreviations are provided in Table 3.Table 4 provides the Blattner numbers for each gene. Genes Encoding theReaction Enzyme(s) Catalyzing Abbreviation Each Reaction* Enzyme nameReaction Stoichiometry ACKr ackA, tdcD acetate kinase [c]: ac + atp <==>actp + adp ADHEr adhE acetaldehyde-CoA dehydrogenase [c]: accoa + (2)h + (2) nadh <==> coa + etoh + (2) nad AKGD sucAB 2-oxoglutaratedehydrogenase [c]: akg + coa + nad --> co2 + nadh + succoa ALCD19 adhCalcohol dehydrogenase (glycerol) [c]: glyald + h + nadh <==> glyc + nadATPS4r atpABCDEFGH ATP synthase (four protons for one ATP) adp[c] + (4)h[e] + pi[c] <==> atp[c] + (3) h[c] + h2o[c] DRPA deoCdeoxyribose-phosphate aldolase [c]: 2dr5p --> acald + g3p EDA eda2-dehydro-3-deoxy-phosphogluconate [c]: 2ddg6p --> g3p + pyr aldolaseENO eno enolase [c]: 2pg <==> h2o + pep F6PA talC, fsa fructose6-phosphate aldolase [c]: f6p <==> dha + g3p FBA fbaA, fbaB, b1773fructose-bisphosphate aldolase [c]: fdp <==> dhap + g3p FBP fbp, glpXfructose-bisphosphatase [c]: fdp + h2o --> f6p + pi FRD frdABCD, sdhABCDfumarate reductase [c]: fum + mql8 --> mqn8 + succ FUM fumA, fumB, fumCfumarase [c]: fum + h2o <==> mal-L G6PDHy zwf glucose 6-phosphatedehydrogenase [c]: g6p + nadp <==> 6pgl + h + nadph GAPD gapA, gapCglyceraldehyde-3-phosphate dehydrogenase [c]: g3p + nad + pi <==>13dpg + h + nadh (NAD) GLCDe gcd Glucose dehydrogenase (ubiquinone-8 asglc-D[e] + h2o[e] + ubq8[c] --> glcn-D[e] + h[e] acceptor) + ubq8h2[c]GLCpts ptsG D-glucose transport via PEP:Pyr PTS glc-D[e] + pep[c] -->g6p[c] + pyr[c] HEX1 glk hexokinase (D-glucose:ATP) [c]: atp + glc-D -->adp + g6p + h LDH_D ldhA, dld D-lactate dehydrogenase [c]: lac-D + nad<==> h + nadh + pyr MGSA mgsA methylglyoxal synthase [c]: dhap -->mthgxl + pi PGDH gnd phosphogluconate dehydrogenase [c]: 6pgc + nadp -->co₂ + nadph + ru5p-D PDH aceEF pyruvate dehydrogenase [c]: coa + nad +pyr --> accoa + co2 + nadh PFL pflA, pflB, tdcE pyruvate formate lyase[c]: coa + pyr --> accoa + for PGDHY edd phosphogluconate dehydratase[c]: 6pgc --> 2ddg6p + h2o PGI pgi glucose-6-phosphate isomerase [c]:g6p <==> f6p PGK pgk, gpmA, gpmB phosphoglycerate kinase [c]: 13dpg +adp <==> 3pg + atp PGL pgl 6-phosphogluconolactonase [c]: 6pgl + h2o -->6pgc + h PGM yibO phosphoglycerate mutase [c]: 3pg <==> 2pg PTAr ptaphosphotransacetylase [c]: accoa + pi <==> actp + coa SUCOAS sucCDsuccinyl-CoA synthetase (ADP-forming) [c]: atp + coa + succ <==> adp +pi + succoa TPI tpi triose-phosphate isomerase [c]: dhap <==> g3p THD2pntA, pntB NAD(P) transhydrogenase (2) h[e] + nadh[c] + nadp[c] --> (2)h[c] + nad[c] + nadph[c]

TABLE 3 Metabolite names corresponding to abbreviations from Table 2.Metabolite Abbre- viation Compartment Metabolite Name 13dpg Cytosol3-Phospho-D-glyceroylphosphate 2ddg6p Cytosol2-Dehydro-3-deoxy-D-gluconate6-phosphate 2dr5p Cytosol2-Deoxy-D-ribose5-phosphate 2pg Cytosol D-Glycerate2-phosphate 3pgCytosol 3-Phospho-D-glycerate 6pgc Cytosol 6-Phospho-D-gluconate 6pglCytosol 6-phospho-D-glucono-1,5-lactone ac Cytosol Acetate acald CytosolAcetaldehyde accoa Cytosol Acetyl-CoA actp Cytosol Acetylphosphate adpCytosol ADP akg Cytosol 2-Oxoglutarate atp Cytosol ATP co2 Cytosol CO2coa Cytosol CoenzymeA dha Cytosol Dihydroxyacetone dhap CytosolDihydroxyacetonephosphate etoh Cytosol Ethanol f6p CytosolD-Fructose6-phosphate fdp Cytosol D-Fructose1,6-bisphosphate for CytosolFormate fum Cytosol Fumarate g3p Cytosol Glyceraldehyde3-phosphate g6pCytosol D-Glucose6-phosphate glc-D[e] Extra-organism D-Glucose glcn-D[e]Extra-organism D-Gluconate glyald Cytosol D-Glyceraldehyde glyc CytosolGlycerol h Cytosol H+ h[e] Extra-organism H+ h2o Cytosol H2O h2o[e]Extra-organism H2O lac-D Cytosol D-Lactate mal-L Cytosol L-Malate mql8Cytosol Menaquinol8 mqn8 Cytosol Menaquinone8 mthgxl CytosolMethylglyoxal nad Cytosol Nicotinamideadeninedinucleotide nadh CytosolNicotinamideadeninedinucleotide- nadp CytosolNicotinamideadeninedinucleotidephosphate nadph CytosolNicotinamideadeninedinucleotidephosphate pep Cytosol Phosphoenolpyruvatepi Cytosol Phosphate pyr Cytosol Pyruvate ru5p-D CytosolD-ribulose-5-phosphate succ Cytosol Succinate succoa CytosolSuccinyl-CoA ubq8 Cytosol Ubiquinone-8 ubq8h2 Cytosol Ubiquinol-8

TABLE 4 Corresponding Blattner numbers for each gene name. Gene NamesBlattner numbers aceEF b0114, b0115 ackA b2296 adhC b0356 adhE b1241atpABCDEFGHI b373, b3732, b3733, b3734, b3735, b3736, b3737, b3738,b3739 b1773 b1773 deoC b4381 dld b2133 eda b1850 edd b1851 eno b2779fbaA b2925 fbaB b2097 fbp b4232 frdABCD b4151, b4152, b4153, b4154 fsab0825 fumA b1612 fumB b4122 fumC b1611 gapA b1779 gapC b1416, b1417 gcdb0124 glk b2388 glpX b3925 gnd b2029 gpmA b0755 gpmB b4395 ldhA b1380mgsA b0963 pflAB b0902, b0903 pgi b4025 pgk b2926 pgl b0767 pntAB b1602,b1603 pta b2297 ptsG b1101 sdhABCD b0721, b0722, b0723, b0724 sucABb0726, b0727 sucCD b0728, b0729 talC b3946 tdcD b3115 tdcE b3114 tpib3919 yibO b3612 zwf b1852

Growth-Coupled 3-HP Production Using the Anaerobic β-Alanine Pathway:

The first set of identified knockout designs described in this sectionare directed to the removal of various combinations of genes responsiblefor the production of the fermentation products acetate (ackA-pta),ethanol (adhE), lactate (ldhA), and succinate (frdABCD). In particular,six growth-coupled 3-HP producing designs are described whose productioncapabilities are shown in FIG. 5. The six growth-coupled 3-HP producingstrains are:

-   -   #1) adhE, ldhA, pta-ackA (ADHEr, LDH_D, PTAr and/or ACKr)    -   #2) adhE, ldhA, frdABCD (ADHEr, LDH_D, FRD)    -   #3) adhE, ldhA, frdABCD, ptsG (ADHEr, LDH_D, FRD, GLCpts)    -   #4) adhE, ldhA, frdABCD, pntAB (ADHEr, LDH_D, FRD, THD2)    -   #5) adhE, ldhA, fumA, fumB, fumC (ADHEr, LDH_D, FUM)    -   #6) adhE, ldhA, fumA, fumB, fumC, pntAB (ADHEr, LDH_D, FUM,        THD2)

A final mass yield can be increased to about 90% by further evolvingmicroorganisms engineered to contain these activity changes towardstheir maximum growth rate (i.e., right most portion of solutionboundaries in FIG. 5). Eliminating either the phosphotransferase systemfor glucose uptake (i.e., ptsG) or the proton pumping NAD(P)transhydrogenase (i.e., pntAB) in addition to the deletions of designs#2 can further lead to strains that require the production of 3-HP atany possible growth rate. FIG. 5B shows that combining deletions in thefumarase genes with adhE and ldhA provides an alternative to couplingthese deletions with frdABCD. With respect to sdhABCD deficient strains,one useful procedure is to deleted sdhABCD prior to evolution of strainsfurther containing ΔfrdABCD because, although sdhABCD expression isrepressed under anaerobic conditions, this activity has the capabilityto complement frdABCD provided its expression is adequate (Maklashina etal., J. Bacteriol. 180:5989-96 (1998)).

The second set of identified knockout designs for the β-alanineproduction route utilizes the deletion of both pyruvate dehydrogenase(aceEF) and pyruvate formate lyase (pflAB) in place of ethanoldehydrogenase (adhE). Four of such growth-coupled 3-HP producing designsare described whose production capabilities are shown in FIG. 6. Thefour growth-coupled 3-HP producing strains are:

-   -   #7) aceEF, pflAB, ldhA (PDH, PFLi, LDH_D)    -   #8) aceEF, pflAB, ldhA, ptsG (PDH, PFLi, LDH_D, GLCpts)    -   #9) aceEF, pflAB, ldhA, ptsG, frdABCD (PDH, PFLi, LDH_D, GLCpts)    -   #10) aceEF, pflAB, ldhA, frdABCD (PDH, PFLi, LDH_D, FRD)

Although pyruvate dehydrogenase is repressed under anaerobic conditions,its deletion can prevent evolution from increasing its expression. Incontrast, the rationale for the above designs is based on the jointremoval of pyruvate dehydrogenase and pyruvate formate lyase to create ametabolic bottleneck at pyruvate, a precursor in the anaerobic β-alanineproduction pathway. Thus, these strains can have a simpler evolutionarytrajectory towards 3-HP formation than the strains described by designs#1 though #6 above. The complete reliance of growth on 3-HP productionis achieved with the deletion of ldhA, frdABCD, and ptsG in addition toaceEF and pflAB.

A third set of identified knockout designs for the β-alanine productionroute utilizes removal of phosphoglucose isomerase (pgi) along with adhEand ldhA. This deletion combination forces reliance on the EntnerDoudoroff (ED) pathway for substrate utilization. Three exemplarystrains are set forth below as strain numbers 11-13. FIG. 7 shows thegrowth-coupled production of 3-HP in these strains and shows that thosestrains having growth requirements of at least a 20% 3-HP yield can begenerated by the removal of frdABCD or glk in addition to adhE, ldhA,and pgi. However, the coupling of 3-HP production at optimal growth isrelatively less tight, indicating less production stability evenfollowing evolution. Reliance on the ED pathway is a useful alternativein E. coli hosts even in light of this organism's preference to utilizeEmbden-Meyerhoff-Parnas (EMP) glycolysis under general fermentationconditions.

-   -   #11) adhE, ldhA, pgi (ADHEr, LDH_D, PGI)    -   #12) adhE, ldhA, pgi, glk (ADHEr, LDH_D, PGI, HEX1)    -   #13) adhE, ldhA, pgi, frdABCD (ADHEr, LDH_D, PGI, FRD)

Growth-Coupled 3-HP Production Using the Aerobic Glycerol Pathway:

An initial gene deletion design for invoking growth-coupled productionof 3-HP through the glycerol pathway forces reaction flux through theinitial steps of glycolysis by removing access to the oxidative branchof the pentose phosphate pathway (zwf). This design then halves theglycolytic flow after fructose-1,6-diphosphate via the triose phosphateisomerase (tpi) deletion. An exemplary growth-coupled 3-HP producingstrain utilizing this glycerol pathway is:

-   -   #14) tpi, zwf, adhC, gcd, mgsA, deoC (TPI, G6PDHy, ALCD19,        GLCDe, MGSA, DRPA)

Half of the glycolytic flux is directed towards product formation whilethe other half is directed towards biomass and energy generation. Theremaining gene knockouts in the above strain either prevent thechanneling of flux away from the 3-HP production pathway or prevent thecircumvention of the two deletions, tpi and zwf. The adhC deletionprevents glyceraldehyde production via glycerol dehydrogenase while themgsA deletion prevents the conversion of dihydroxyacetone phosphate intolactate via the methylglyoxal pathway. The deoC deletion prevents anunlikely degradation pathway from ribose-5-phosphate toglyeraldehyde-3-phosphate and acetyl-CoA from draining carbon away fromthe product pathway. The removal of gcd prevents a potential bypass ofthe zwf deletion that involves the conversion of glucose to gluconatewhich can be phosphorylated by gluconate kinase and enter the pentosephosphate pathway at 6-phosphogluconate.

FIG. 8A shows the growth-coupled production of 3-HP for the above strainand indicates that the tpi deletion can impose a ceiling of about 1 mol3-HP/mol glucose on the maximum achievable 3-HP yield. In addition,despite the imposed deletions, glycerol secretion can theoreticallycompete with 3-HP production. However, it is likely that evolution undergrowth selective pressures will select for 3-HP production over glycerolproduction because one NADH is generated by converting glycerol to 3-HP.

Two additional designs employing growth-coupled production of 3-HPthrough the glycerol pathway utilize the elimination ofglyceraldehyde-3-phosphate dehydrogenase (gapA, gapC) which forces themetabolic network to rely on the ED pathway for pyruvate generation.These designs are shown below as strains 15 and 16 and their 3-HPgrowth-coupled production results are shown in FIG. 8B.

-   -   #15) fbp, glpX, gapA, gapC, adhC, mgsA, fsa, talC (FBP, GAPD,        ALCD19, F6PA, MGSA, F6PA)    -   #16) fbp, glpX, gapA, gapC, adhC, mgsA, fsa, talC, gcd (FBP,        GAPD, ALCD19, MGSA, F6PA, GLCDe)

For the engineered cells are to attain optimal growth, the ED fluxtowards glyceraldehyde-3-phosphate is directed towards productformation, while the flux towards pyruvate is used to generate energyand reducing equivalents from the TCA cycle. The fbp, fsa, and talCdeletions prevent the flux from glyceraldehyde-3-phosphate from passingthrough a sequence of gluconeogenic reaction steps, and thus render theproduction of 3-HP more energetically favorable. The adhC, mgsA, gcddeletions serve to prevent the loss of carbon flux through alternativedegradation routes.

The final design for the glycerol-based production route centers onlimiting the flux through glyceraldehyde-3-phosphate dehydrogenase andblocking the ED pathway by deleting edd or eda.

-   -   #17) pgi, edd, adhC, mgsA, gcd, deoC (PGI, PGDHy, ALCD19, MGSA,        GLCDe, DRPA)

The above design sets a control point at glyceraldehyde-3-phosphatewhere any flux through glyceraldehyde-3-phosphate dehydrogenase isdirected towards biomass formation. The remaining flux throughglyceraldehyde-3-phosphate is directed towards the 3-HP productionpathway. The pgi knockout is only necessary only if its direction invivo is towards glucose-6-phosphate. As with the previous designs, thedeletions of adhC, mgsA, gcd, and deoC prevent the loss of carbonthrough alternative degradation routes.

Growth-Coupled 3-HP Production Using the Glycerate Pathway:

The glycerate designs were determined under conditions where theformation of glycerate from 3-phosphoglycerate leads to the productionof one ATP molecule. Accordingly, the net conversion of3-phosphoglycerate to 3-HP results in the regeneration of 1 NADH fromNAD and 1 ATP. In terms of energy and redox yields, this pathway becomesequivalent to the anaerobic production route through β-alanine meaningthat all designs described above under the anaerobic β-alanine pathwayalso are applicable here under anaerobic conditions. For example, theproduction envelope for design #2 using a functional glycerate pathwayto 3-HP in E. coli reveals a strong coupling between 3-HP and growth(see FIG. 10A). However, in addition to the designs described aboveunder the anaerobic β-alanine pathway, the removal of enolase (eno) orphosphoglycerate mutase (yibO) also serves to tightly couple cell growthto 3-HP production.

-   -   #18) eno or yibO (ENO or PGM)

Either knockout can prevent ATP generation through substrate levelphosphorylation leading to the reliance on the 3-HP production pathwayto generate energy. Another useful set of designs involves thesimultaneous removal of enolase (eno) and ATP synthase (atpABCDEFGHI).

-   -   #19) atpABCDEFGHI, eno or yibO, aceEF, pflA, pflB (ATPS4r, ENO        or PGM, PDH, PFLi)    -   #20) atpABCDEFGHI, eno or yibO, sucCD or sucAB, pta-ackA        (ATPS4r, ENO or PGM, SUCOAS or AKGD, PTAr)

When the enolase and ATP synthase knockouts are combined with additionalknockouts to limit the flux through the TCA cycle or towards acetateproduction, the production of glycerate becomes needed for energygeneration and cell growth (see FIG. 10B). Moreover, the strainsconstructed based on designs #19-20 are stable regardless ofoxygenation, making them well-suited for a large-scale industrialprocess which is difficult to keep completely anaerobic but expensive toaerate.

Validation:

In order to coorborate the computational strains identified by themethods of the invention, the strains are constructed, adaptivelyevolved and tested for 3-HP synthesis and/or accumulated levels.Construction of the strains can be performed by using methods well knownin the art and/or by using commercial services available in the art. ForE. coli based strains, Escherichia coli K-12 MG1655 can be used as thewild-type strain into which the deletions are introduced. The strainscan be constructed by, for example, incorporating in-frame deletionsusing homologous recombination via the λ Red recombinase system ofDatsenko and Wanner (Proc Natl Acad Sci USA 97:6640-45 (2000)). Thisapproach involves replacing a chromosomal sequence (i.e., the genetargeted for removal) with a selectable antibiotic resistance gene,which itself is later removed. The knockouts can be integrated one byone into the recipient strain. No drug resistance markers or scars willremain after each deletion allowing accumulation of multiple mutationsin each target strain. Deletion technology can completely remove thegene targeted for removal so as to substantially reduce the possibilityof the constructed mutants reverting back to the wild-type.

The engineered strains can be characterized by, for example, measuringgrowth rate, substrate uptake rate, and/or product/byproduct secretionrate. The initial strains can exhibit suboptimal growth rates untiltheir metabolic networks have adjusted to their missing functionalities.To enable this adjustment, the strains can be adaptively evolved. Bysubjecting the strains to adaptive evolution, cellular growth ratebecomes the primary selection pressure and the modified cells arecompelled to reallocate their metabolic fluxes in order to enhance theirrates of growth. This reprogramming of metabolism has been demonstratedfor several in silico model strains that had been adaptively evolved onvarious substrates to reach the growth rates predicted a priori by thein silico model (Fong S. S., and B. O. Palsson, Nat Genet, 36:1056-58(2004)). The growth improvements brought about by adaptive evolution ofthe constructed strains identified by the methods of the invention willbe accompanied by enhanced rates of 3-HP production. Adaptive evolutionalso can be performed in triplicate (running in parallel) to minimizeany differences in the evolutionary patterns that might impact theextent of adjustment to optimal growth characteristics (see, forexample, Fong and Palsson, supra; Fong et al., J Bacteriol 185:6400-08(2003)), and Ibarra et al., Nature 420:186-89 (2002)). Hence, strainsresulting in superior production qualities over another can beidentified from the triplicate samples. Evolutions can be run for aperiod of 2-6 weeks, depending on the rate of growth improvementobtained. In general, evolutions will be stopped once a stable growthphenotype is obtained.

Following the adaptive evolution process, the new strains can again becharacterized by, for example, measuring growth rate, substrate uptakerate and/or product/byproduct secretion rate. These results can becompared to the strains identified by the methods of the invention byplotting actual growth and production yields along side the productionenvelopes in the figures set forth herein. The most successful OptKnockdesign/evolution combinations can be chosen to pursue further, and canbe characterized in lab-scale batch and continuous fermentations. Thegrowth-coupled biochemical production concept behind the OptKnockapproach should also result in the generation of genetically stableoverproducers. Thus, the cultures can be maintained in continuous modefor one month to evaluate long-term stability. Periodic samples can betaken to ensure that yield and productivity are maintained throughoutthe experiment.

Summary:

Gene deletion designs for increasing 3-HP production in an exemplary E.coli host microorganism have been identified. Evolution of these designstowards the designed end points is particularly useful in combinationwith identification and metabolic engineering of strains havinggrowth-coupled production of products such as 3-HP. The computationalsystem of the invention also is particularly useful for such commercialapplications because it can identify non-intuitive knockouts byconsidering the entire metabolic network of E. coli.

Throughout this application various publications have been referencedwithin parentheses. The disclosures of these publications in theirentireties are hereby incorporated by reference in this application inorder to more fully describe the state of the art to which thisinvention pertains.

Although the invention has been described with reference to thedisclosed embodiments, those skilled in the art will readily appreciatethat the specific examples and studies detailed above are onlyillustrative of the invention. It should be understood that variousmodifications can be made without departing from the spirit of theinvention. Accordingly, the invention is limited only by the followingclaims.

What is claimed is:
 1. An isolated non-naturally occurring microorganismcomprising a set of gene disruptions coupling 3-hydroxypropionic acidproduction to growth of said microorganism, wherein said microorganismutilizes an anaerobic β-alanine 3-HP precursor pathway and said set ofgene disruptions comprise a disruption of one or more pflAB genes and adisruption of a ldhA gene, wherein said microorganism comprises stablegrowth-coupled production of 3-hydroxypropionic acid.
 2. The isolatednon-naturally occurring microorganism of claim 1, wherein said set ofgene disruptions further comprise a disruption of one or more aceEFgenes, a disruption of one or more ptsG genes or a disruption of one ormore frdABCD genes.
 3. The isolated non-naturally occurringmicroorganism of claim 1, wherein said disruption of one or more genescomprises a deletion.
 4. The isolated non-naturally occurringmicroorganism of claim 1, wherein said microorganism comprises abacterium, yeast or fungus.
 5. The isolated non-naturally occurringmicroorganism of claim 4, wherein said bacteria comprises a speciesselected from E. coli, A. succiniciproducens, A. succinogenes, Msucciniciproducens, R. etli, Bacillus subtilis, Corynebacteriumglutamicum, Gluconobacter oxydans, Zymomonas mobilis, Lactococcuslactis, Lactobacillus plantarum, Streptomyces coelicolor, Clostridiumacetobutylicum, Pseudomonas fluorescens, Klebsiella oxytoca, andPseudomonas putida.
 6. The isolated non-naturally occurringmicroorganism of claim 4, wherein said yeast comprises a speciesselected from Saccharomyces cerevisiae, Schizosaccharomyces pombe,Kluyveromyces lactis, Kluyveromyces marxianus, Penicilium chrysogenum,Aspergillus terreus, Aspergillus niger, and Pichia pastoris.
 7. Theisolated non-naturally occurring microorganism of claim 2, wherein saidset of gene disruptions comprise a disruption of one or more pflABgenes, a disruption of a ldhA gene and a disruption of one or more aceEFgenes.
 8. The isolated non-naturally occurring microorganism of claim 2,wherein said set of gene disruptions comprise a disruption of one ormore pflAB genes, a disruption of a ldhA gene, a disruption of one ormore aceEF genes and a disruption of one or more ptsG gene.
 9. Theisolated non-naturally occurring microorganism of claim 2, wherein saidset of gene disruptions comprise a disruption of one or more pflABgenes, a disruption of a ldhA gene, a disruption of one or more aceEFgenes and a disruption of one or more frdABCD genes.
 10. The isolatednon-naturally occurring microorganism of claim 2, wherein said set ofgene disruptions comprise a disruption of one or more pflAB genes, adisruption of a ldhA gene, a disruption of one or more aceEF genes, adisruption of one or more ptsG genes and a disruption of one or morefrdABCD genes.